Senior ML Engineer

Company Description

Soojh AI is a leading AI services and consulting firm dedicated to helping businesses leverage the power of Artificial Intelligence and Generative AI for scalable efficiency. We offer end-to-end expertise for integrating AI into operations, building AI-driven products, or setting up in-house AI Labs and AI teams. Our track record includes successful collaborations with Fortune 500 companies and high-growth startups across various sectors such as FinTech, LegalTech, Healthcare, Media, Hospitality, and Airlines.

Role Description

This is a full-time role for a Senior ML Engineer based in Bangalore or New Delhi. The Senior ML Engineer will be responsible for designing, developing, and deploying cutting-edge Machine Learning and Generative AI (GenAI) solutions. The role requires strong technical expertise in building scalable ML systems, developing GenAI applications, and evaluating their performance using advanced AI evaluation frameworks. The engineer will work closely with cross-functional teams to translate business requirements into impactful AI solutions, while mentoring junior engineers and staying ahead of emerging trends in ML and GenAI technologies.

Key Responsibilities

1. Design, develop, and deploy advanced Machine Learning and Generative AI models for production.
2. Collaborate with data scientists, engineers, and stakeholders to build scalable, data-driven solutions.
3. Evaluate AI model performance using structured AI evaluation frameworks such as RAGAS.
4. Conduct research and experimentation to improve accuracy, efficiency, and interpretability of models.
5. Integrate LangChain or similar frameworks to enhance LLM-based solutions (good to have).
6. Contribute to establishing best practices for model governance, testing, and deployment.
7. Mentor junior engineers and promote innovation across the AI/ML team.

Qualifications

1. Proven expertise in Generative AI and Machine Learning model development
2. Strong skills in Time Series forecasting and traditional ML algorithms
3. Proficiency in Computer Science fundamentals, Data Structures, Algorithms, and Statistics
4. Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
5. Familiarity with LangChain or similar GenAI development tools (good to have)
6. Hands-on experience with AI evaluation frameworks, particularly RAGAS
7. Strong problem-solving, analytical, and collaboration skills